2. Materials and Methods
As the European Union is dependent on coking coal imports, Prairie Mining Ltd.’s plan for the Dębieńsko project is to produce 2.6 Mtpa of premium hard coking coal from the start of production. Prairie Mining Ltd. is going to use underground longwall mining, which has been used in Poland for a long time. The mine is projected to produce 4 Mtpa during the Run of Mine (RoM), with two longwalls to be mined simultaneously in different parts of the mine [
17]. The total coal resources according to the Joint Ore Reserves Committee (JORC) Code [
18] are shown in
Table 2.
The production was planned to ramp up four years after the beginning.
Table 3 shows the assumed production parameters.
In order to analyze these data, the work developed by Matyjaszek et al. [
20] was used. It was based on five ready-to-go projects worldwide: Lublin in Poland, Kodiak in the USA, Amaam in Russia, Makhado in South Africa, and Crown Mountain in Canada. In this work, the authors develop an exhaustive analysis of coking coal mining investment, providing a tool to allow quick discrimination between feasible and non-feasible projects.
Precisely, they were able to establish a relationship between capital expenses (CAPEX) and clean coking coal production:
Operating costs were assessed based on the yield and the transport costs:
Mining costs in
$/t of saleable coal of the different projects were assessed based on the operating costs:
Also, they conclude that appropriate discount rates should be used, and disclosure of how price forecasting should be developed is described in the paper.
In turn, this paper is based on the seminal work by Suárez Sánchez et al. [
21] and by Riesgo García et al. [
22].
Suárez Sánchez et al. [
21] analyzed investments in tungsten mining based on the analysis of five ready-to-go projects worldwide: Barruecopardo in Spain, Kilba in Australia, Hemerdon in the United Kingdom, Sangdong in South Korea, and King Island Scheelite in Tasmania. This analysis established relationships between the CAPEX and the operating expenses (OPEX) based on the mining and processing parameters.
For its part, Riesgo García et al. [
22] analyzed rare earth mining projects worldwide, studying five ready-to-go projects again: Nechalacho in Canada, Zandkopsdrift in South Africa, Bear Lodge in the USA, Kvanefjeld in Greenland, and Dubbo Zirconia in Australia. They established a relation between CAPEX, processing tons and processing grade, and different relations for OPEX (mining costs, processing costs, and separating costs) with the mining tons, the processing tons and the different processing grades.
Later, a work by Sterba et al. [
23] was also based on these seminal works. Sterba et al. analyzed the technical and economic magnitudes of lithium mining projects, based again on five ready-to-go projects worldwide: Whabouchi in Canada, Keliber in Finland, Cauchari-Olaroz in Argentina, Sonora in Mexico, and Pilgangoora in Australia. They established a correlation between the CAPEX and lithium carbonate production and different relations for the OPEX.
The seminal work by Riesgo García et al. [
22], as well as the work by Sterba et al. [
23], were contrasted by analyzing specific mining projects: in the first case, the Sarfartoq rare earth element project in Greenland [
24], and in the second case, the Cínovec lithium mining project in the Czech Republic [
25]. Thus, this paper will be based on a sound theoretical background, contributing with a specific analysis not yet developed in coking coal mining investment.
To estimate the financial outcomes, Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period (PP) will be determined in order to establish the feasibility of the project. As a specific funding scheme should be developed for any investment, the NPV should be determined using the weighted average cost of capital (WACC) [
26]. Nevertheless, according to the AIM Rules—Guidance for Mining and Oil & Gas Companies [
27], a 10% discount rate (post-tax) should be appropriate for this purpose.
Risk analysis techniques have long been recognized as powerful tools to help decision-makers successfully manage situations subject to uncertainty. In the first place sensitivity analysis, a risk assessment process that predicts the result using variables that affect the outcome, was developed using the software TopRank 7.5 (Palisade Corporation, New York, NY, USA). TopRank performs automated “what if” sensitivity analysis on Microsoft Excel spreadsheets to answer what variables affect the most. TopRank finds and varies all input cells that affect the output, with a result easy-to-understand through tornado charts, spider graphs, and other reports that identify and rank, which affect the outcome the most.
Mostly, sensitivity analysis is followed by an uncertainty analysis, which quantifies uncertainty in model outcomes.
An uncertainty analysis focuses on quantifying uncertainty in model outputs. To provide decision makers with useful information, it is necessary to generate a comprehensive range of potential outcomes and relative probabilities. This approach allows the best possible decisions to be made. A Monte Carlo simulation is typically used when conducting an uncertainty analysis on critical variables. This simulation approach involves a computerized mathematical technique that allows one to account for risks involved in the quantitative analysis and the decision making. @RISK 7.5 (Palisade Corporation, New York, NY, USA) was the software used for the simulation. @RISK has advanced capabilities for specifying and executing simulations of Excel models. Both Monte Carlo and Latin Hypercube sampling techniques are supported, and distributions of possible results may be generated for any cell or range of cells in the spreadsheet model. High-resolution graphics are used to present the output distributions: histograms, cumulative curves, and summary graphs.
In order to develop the economic analysis, the assumptions presented here were used.
Table 4 presents the assumptions for the life of mine, yield, and clean coal production. They were taken from the scoping study for the fully permitted Debiensko mine [
17].
Relating royalties and according to the Geological and Mining Law [
28], a mining area is designated for each mineral in Poland. Within such an area, the mine obtains the right to extract minerals for a given time. This right is included in the concession to exploit the deposit granted by the minister responsible for environmental affairs. Granting a concession obliges the mine to pay an operating fee. This fee is calculated as the product of the exploitation rate and the extraction volume in a given year. The rate limits are determined by the minister responsible for the environment and depend on the type of mineral. The level of royalties for coking coal is 0.80
$/t.
Finally, metallurgical coal prices were relatively stable in 2018, starting at just over 250
$/t, drifting down to 175
$/t in August and recovering by year-end to around 200
$/t free on board (FOB) for Australian prime hard coking coal [
29]. A conservative 100
$/t price will be considered to prevent drastic price reductions of 75
$/t in 2018.
4. Conclusions
Coking coal is a critical raw material for the EU that is still needed by the steel industry. There are no clear alternative solutions for this electricity-intensive industry, as neither electrification nor improvements in materials or energy efficiency are yet available at a sufficient Technology Readiness Level (TRL). On the other hand, coking coal “substitution index” that measures the difficulty of replacing the material, scored and weighted across all applications, is 0.92 according to the EU, with values between zero and one, one being the least substitutable, and there is no possibility of recycling coking coal. These factors indicate that the European Union remains dependent on coking coal imports, with domestic production covering only 37% of its consumption.
Therefore, any coking coal mining project in Europe id an answer to the existing demand in Europe. Specifically, this article analyses the coking coal mining project in Poland called Dębieńsko, using a scientifically proven methodology based on a world-class analysis of coking coal mining projects that have been submitted to financial markets for financing.
The calculations made based on this world-class analysis of coking coal mining projects show that the internal although of smaller dimension, Dębieńsko project has an after-tax internal rate of return of 28.0%, more significant than 26.6% from Lublin project although with a higher payback period: five and three years, respectively.
Risk analysis techniques have long been recognized as powerful tools to help decision-makers successfully manage situations subject to uncertainty. The variable with the most significant impact on NPV is the coking coal price, followed by the clean coal production and the discount rate, with similar influence weights.
After modelling probability distributions for coking coal price and clean coal production, a Monte Carlo analysis was developed. The NPV distribution result has a mean value of 954 M$, thus improving the Net Present Value calculated via the cash-flows (660 M$), far outweighing the uncertainty analysis.
It is clear from the analysis of this project that its profitability is even higher than that of the most critical mining projects currently underway, such as Lublin, also in Poland. Also, Dębieńsko has successfully passed the most rigorous risk analysis that can be performed and is directly related to the price of this raw material.